Ocean variability and its influence on the detectability of greenhouse warming signals

Recent investigations have considered whether it is possible to achieve early detection of greenhouse-gas-induced climate change by observing changes in ocean variables. In this study we use model data to assess some of the uncertainties involved in estimating when we could expect to detect ocean greenhouse warming signals. We distinguish between detection periods and detection times. As defined here, detection period is the length of a climate time series required in order to detect, at some prescribed significance level, a given linear trend in the presence of the natural climate variability. Detection period is defined in model years and is independent of reference time and the real time evolution of the signal. Detection time is computed for an actual time-evolving signal from a greenhouse warming experiment and depends on the experiment's start date. Two sources of uncertainty are considered: those associated with the level of natural variability or noise, and those associated with the time-evolving signals. We analyze the ocean signal and noise for spatially averaged ocean circulation indices such as heat and fresh water fluxes, rate of deep water formation, salinity, temperature, transport of mass, and ice volume. The signals for these quantities are taken from recent time-dependent greenhouse warming experiments performed by the Max Planck Institute for Meteorology in Hamburg with a coupled ocean-atmosphere general circulation model. The time-dependent greenhouse gas increase in these experiments was specified in accordance with scenario A of the Intergovernmental Panel on Climate Change. The natural variability noise is derived from a 300-year control run performed with the same coupled atmosphere-ocean model and from two long (>3000 years) stochastic forcing experiments in which an uncoupled ocean model was forced by white noise surface flux variations. In the first experiment the stochastic forcing was restricted to the fresh water fluxes, while in the second experiment the ocean model was additionally forced by variations in wind stress and heat fluxes. The mean states and ocean variability are very different in the three natural variability integrations. A suite of greenhouse warming simulations with identical forcing but different initial conditions reveals that the signal estimated from these experiments may evolve in noticeably different ways for some ocean variables. The combined signal and noise uncertainties translate into large uncertainties in estimates of detection time. Nevertheless, we find that ocean variables that are highly sensitive indicators of surface conditions, such as convective overturning in the North Atlantic, have shorter signal detection times (35?65 years) than deep-ocean indicators (≥100 years). We investigate also whether the use of a multivariate detection vector increases the probability of early detection. We find that this can yield detection times of 35?60 years (relative to a 1985 reference date) if signal and noise are projected onto a common ?fingerprint? which describes the expected signal direction. Optimization of the signal-to-noise ratio by (spatial) rotation of the fingerprint in the direction of low-noise components of the stochastic forcing experiments noticeably reduces the detection time (to 10?45 years). However, rotation in space alone does not guarantee an improvement of the signal-to-noise ratio for a time-dependent signal. This requires an ?optimal fingerprint? strategy in which the detection pattern (fingerprint) is rotated in both space and time

Comparative genomics reveals distinct host-interacting traits of three major human-associated propionibacteria

BACKGROUND: Propionibacteria are part of the human microbiota. Many studies have addressed the predominant colonizer of sebaceous follicles of the skin, Propionibacterium acnes, and investigated its association with the skin disorder acne vulgaris, and lately with prostate cancer. Much less is known about two other propionibacterial species frequently found on human tissue sites, Propionibacterium granulosum and Propionibacterium avidum. Here we analyzed two and three genomes of P. granulosum and P. avidum, respectively, and compared them to two genomes of P. acnes; we further highlight differences among the three cutaneous species with proteomic and microscopy approaches. RESULTS: Electron and atomic force microscopy revealed an exopolysaccharide (EPS)-like structure surrounding P. avidum cells, that is absent in P. acnes and P. granulosum. In contrast, P. granulosum possesses pili-like appendices, which was confirmed by surface proteome analysis. The corresponding genes were identified; they are clustered with genes encoding sortases. Both, P. granulosum and P. avidum lack surface or secreted proteins for predicted host-interacting factors of P. acnes, including several CAMP factors, sialidases, dermatan-sulphate adhesins, hyaluronidase and a SH3 domain-containing lipoprotein; accordingly, only P. acnes exhibits neuraminidase and hyaluronidase activities. These functions are encoded on previously unrecognized island-like regions in the genome of P. acnes. CONCLUSIONS: Despite their omnipresence on human skin little is known about the role of cutaneous propionibacteria. All three species are associated with a variety of diseases, including postoperative and device-related abscesses and infections. We showed that the three organisms have evolved distinct features to interact with their human host. Whereas P. avidum and P. granulosum produce an EPS-like surface structure and pili-like appendices, respectively, P. acnes possesses a number of unique surface-exposed proteins with host-interacting properties. The different surface properties of the three cutaneous propionibacteria are likely to determine their colonizing ability and pathogenic potential on the skin and at non-skin sites

Fractional Langevin equation

We investigate fractional Brownian motion with a microscopic random-matrix model and introduce a fractional Langevin equation. We use the latter to study both sub- and superdiffusion of a free particle coupled to a fractal heat bath. We further compare fractional Brownian motion with the fractal time process. The respective mean-square displacements of these two forms of anomalous diffusion exhibit the same power-law behavior. Here we show that their lowest moments are actually all identical, except the second moment of the velocity. This provides a simple criterion which enables to distinguish these two non-Markovian processes.Comment: 4 page

Elucidation of the Structure of Solanoeclepin A, a Natural Hatching Factor of Potato and Tomato Cyst Nematodes, by Single-crystal X-ray Diffraction

Potato crops can be severely damaged by potato cyst nematodes Globodera rostochiensis and Globodera pallida, nematodes highly specific to potatoes and some other Solanaceae. Hatching of juveniles is controlled by agents excreted by the roots of some Solanaceae species. Over seventy years much effort has been expended by many groups to isolate these agents and to determine their structures. However, all attempts have failed. We report here the structure determination of a hatching factor excreted from potato and tomato roots. The hatching factor bears some resemblance to Glycinoeclepins as found by Masamune et al.2-5 and is hence designated as Solanoeclepin A.1 C27H30O9.3H2O, Mr = 498.5, monoclinic, P21, a = 11.289(2), b = 20.644(4), c = 11.632(12) Å, β = 90.81(4), V = 2711(3) Å3, Z = 4, Dx = 1.35 g cm–3, λ(Cu-K&alpha ) = 1.5418 Å, μ(Cu-Kα ) = 9.0 cm–1, F(000) = 1176, –60 °C. Final R = 0.117 for 3721 observed reflections

Hygroscopic growth of urban aerosol particles in Beijing (China) during wintertime: A comparison of three experimental methods

The hygroscopic properties of atmospheric aerosols are highly relevant for the quantification of radiative effects in the atmosphere, but also of interest for the assessment of particle health effects upon inhalation. This article reports measurements of aerosol particle hygroscopicity in the highly polluted urban atmosphere of Beijing, China in January 2005. The meteorological conditions corresponded to a relatively cold and dry atmosphere. Three different methods were used: 1) A combination of Humidifying Differential Mobility Particle Sizer (H-DMPS) and Twin Differential Mobility Particle Sizer (TDMPS) measurements, 2) A Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA), and 3) A simplistic solubility model fed by chemical particle composition determined from Micro Orifice Uniform Deposit Impactor (MOUDI) samples. From the H-DMPS and TDMPS particle number size distributions, a size-resolved descriptive hygroscopic growth factor (DHGF) was determined for the relative humidities (RH) 55%, 77% and 90%, and particle diameters between 30 and 400 nm. In Beijing, the highest DHGFs were observed for accumulation mode particles, 1.40 (±0.03) at 90% RH. DHGF decreased significantly with particle size, reaching 1.04 (±0.15) at 30 nm. H-TDMA data also suggest a decrease in growth factor towards the biggest particles investigated (350 nm), associated with an increasing fraction of nearly hydrophobic particles. The agreement between the H-DMPS/TDMPS and H-TDMA methods was satisfactory in the accumulation mode size range (100–400 nm). In the Aitken mode range (<100 nm), the H-DMPS/TDMPS method yielded growth factors lower by up to 0.1 at 90% RH. The application of the solubility model based on measured chemical composition clearly reproduced the size-dependent trend in hygroscopic particle growth observed by the other methods. In the case of aerosol dominated by inorganic ions, the composition-derived growth factors tended to agree (± 0.05) or underestimate (up to 0.1) the values measured by the other two methods. In the case of aerosol dominated by organics, the reverse was true, with an overestimation of up to 0.2. The results shed light on the experimental and methodological uncertainties that are still connected with the determination of hygroscopic growth factors

Prevalence of spontaneous, induced labour or planned caesarean section and factors associated with caesarean scetion and factors associated with caesarian section in low-risk women in southern Brazil

Objective This study aimed to examine the prevalence of spontaneous labour, induced labour and planned caesarean section in low-risk women; to identify the contribution of each group to the overall caesarean section rate; and to estimate factors associated with caesarean section in low-risk women according to spontaneous labour, induced labour and planned caesarean section. Design Cross-sectional hospital-based study of postpartum women and newborns, using data from the survey Birth in Brazil, Southern region. In the sample of 2,668 low-risk women, a descriptive analysis was undertaken and a Multinomial Logistic Regression model was applied to verify associations among caesarean section and spontaneous labour, induced labour and planned caesarean section in comparison with vaginal birth. Measurements and Findings The results showed the prevalence of spontaneous labour (48.0%), induced labour (14.0%) and planned caesarean sections (38.0%); these frequencies contributed to an overall caesarean section rate of 50.5%. Obstetric characteristics like previous vaginal birth or previous caesarean section were differentially associated with caesarean section, independently of the labour. Caesarean section without labour was significantly associated with age ≥ 35 years (ORadj 5.45 95%CI 3.16-9.39), economic class A and B (ORadj 3.10 95%CI 1.92-4.99), pregnancy between 37 and 38 weeks (ORadj 1.65 95%CI 1.22-2.24), same obstetrician in prenatal and childbirth (ORadj 13.83 95%CI 8.85-21.61) and private payment source at birth (ORadj 11.50 95%CI 6.64-19.93). Key conclusion For low-risk women in Southern Brazil, the results identify high planned caesarean section rates, not associated with socioeconomic, obstetric, institutional or prenatal factors that justify these rates

Diurnal variations of ambient particulate wood burning emissions and their contribution to the concentration of Polycyclic Aromatic Hydrocarbons (PAHs) in Seiffen, Germany

Residential wood burning is becoming an increasingly important cause of air quality problems since it has become a popular source of alternative energy to fossil fuel. In order to characterize the contribution of residential wood burning to local particle pollution, a field campaign was organized at the village of Seiffen (Saxony, Germany). During this campaign, an Aerosol Mass Spectrometer (AMS) was deployed in parallel to a PM&lt;sub&gt;1&lt;/sub&gt; high volume filter sampler. The AMS mass spectra were analyzed using Positive Matrix Factorization (PMF) to obtain detailed information about the organic aerosol (OA). Biomass-burning organic aerosol (BBOA), Hydrocarbon-like organic aerosol (HOA), and Oxygenated Organic Aerosol (OOA) were identified and represented 20%, 17% and 62% of total OA, respectively. Additionally, Polycyclic Aromatic Hydrocarbons (PAH) were measured by the AMS with an average concentration of 10 ng m&lt;sup&gt;−3&lt;/sup&gt; and short term events of extremely high PAH concentration (up to 500 ng m&lt;sup&gt;−3&lt;/sup&gt;) compared to the mean PAH value were observed during the whole measurement period. A comparison with the results from PM&lt;sub&gt;1&lt;/sub&gt; filter samples showed that the BBOA factor and the AMS PAH are good indicators of the total concentration of the different monosaccharide anhydrides and PAH measured on the filter samples. Based on its low correlation with CO and the low car traffic, the HOA factor was considered to be related to residential heating using liquid fuel. An influence of the time of the week (week vs. weekend) on the diurnal profiles of the different OA components was observed. The weekdays were characterized by two maxima; a first one early in the morning and a stronger one in the evening. During the weekend days, the different OA components principally reached only one maximum in the afternoon. Finally, the PAH emitted directly from residential wood combustion was estimated to represent 1.5% of the total mass of the BBOA factor and around 62% of the total PAH concentration measured at Seiffen. This result highlights the important contribution of residential wood combustion to air quality and PAH emissions at the sampling place, which might have a significant impact on human health. Moreover, it also emphasizes the need for a better time resolution of the chemical characterization of toxic particulate compounds in order to provide more information on variations of the different sources through the days as well as to better estimate the real human exposure

Pan-genome analysis of the genus Finegoldia identifies two distinct clades, strain-specific heterogeneity, and putative virulence factors

Abstract Finegoldia magna, a Gram-positive anaerobic coccus, is an opportunistic pathogen, associated with medical device-related infections. F. magna is the only described species of the genus Finegoldia. We report the analysis of 17 genomes of Finegoldia isolates. Phylogenomic analyses showed that the Finegoldia population can be divided into two distinct clades, with an average nucleotide identity of 90.7%. One clade contains strains of F. magna, whereas the other clade includes more heterogeneous strains, hereafter tentatively named “Finegoldia nericia”. The latter species appears to be more abundant in the human microbiome. Surface structure differences between strains of F. magna and “F. nericia” were detected by microscopy. Strain-specific heterogeneity is high and previously identified host-interacting factors are present only in subsets of “F. nericia” and F. magna strains. However, all genomes encode multiple host factor-binding proteins such as albumin-, collagen-, and immunoglobulin-binding proteins, and two to four copies of CAMP (Christie-Atkins-Munch-Petersen) factors; in accordance, most strains show a positive CAMP reaction for co-hemolysis. Our work sheds new light of the genus Finegoldia and its ability to bind host components. Future research should explore if the genomic differences identified here affect the potential of different Finegoldia species and strains to cause opportunistic infections

Diurnal variations of ambient particulate wood burning emissions and their contribution to the concentration of Polycyclic Aromatic Hydrocarbons (PAHs) in Seiffen, Germany

Residential wood burning is becoming an increasingly important cause of air quality problems since it has become a popular source of alternative energy to fossil fuel. In order to characterize the contribution of residential wood burning to local particle pollution, a field campaign was organized at the village of Seiffen (Saxony, Germany). During this campaign, an Aerosol Mass Spectrometer (AMS) was deployed in parallel to a PM1 high volume filter sampler. The AMS mass spectra were analyzed using Positive Matrix Factorization (PMF) to obtain detailed information about the organic aerosol (OA). Biomass-burning organic aerosol (BBOA), Hydrocarbon-like organic aerosol (HOA), and Oxygenated Organic Aerosol (OOA) were identified and represented 20%, 17% and 62% of total OA, respectively. Additionally, Polycyclic Aromatic Hydrocarbons (PAH) were measured by the AMS with an average concentration of 10 ng m−3 and short term events of extremely high PAH concentration (up to 500 ng m−3) compared to the mean PAH value were observed during the whole measurement period. A comparison with the results from PM1 filter samples showed that the BBOA factor and the AMS PAH are good indicators of the total concentration of the different monosaccharide anhydrides and PAH measured on the filter samples. Based on its low correlation with CO and the low car traffic, the HOA factor was considered to be related to residential heating using liquid fuel. An influence of the time of the week (week vs. weekend) on the diurnal profiles of the different OA components was observed. The weekdays were characterized by two maxima; a first one early in the morning and a stronger one in the evening. During the weekend days, the different OA components principally reached only one maximum in the afternoon. Finally, the PAH emitted directly from residential wood combustion was estimated to represent 1.5% of the total mass of the BBOA factor and around 62% of the total PAH concentration measured at Seiffen. This result highlights the important contribution of residential wood combustion to air quality and PAH emissions at the sampling place, which might have a significant impact on human health. Moreover, it also emphasizes the need for a better time resolution of the chemical characterization of toxic particulate compounds in order to provide more information on variations of the different sources through the days as well as to better estimate the real human exposure